Professor, Department of Electrical Engineering and Computer Science
Polina Golland is a professor in MIT’s Department of Electrical Engineering and Computer Science and leads the Medical Vision Group at the Computer Science and Artificial Intelligence Laboratory. Her main research focus is in developing novel techniques for analyzing and understanding biomedical images. Her interests include algorithms that explore the geometry of the world, process images in new ways and improve image-based inference through statistical modeling of image data. She is interested in shape modeling and representation, predictive modeling and visualization of statistical models. Her current research focuses on developing statistical methods for analyzing and characterizing biological processes based on image information. She earned a PhD in electrical engineering and computer science from MIT.
Chauhan, G., Liao, R., Wells III, W. M., Andreas, J., Wang, X., Berkowitz, S., Horng, S., Szolovits, P., Golland, P. (2020). Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment. International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI).
Wang, C. J., Rost, N. S., Golland, P. (2020). Spatial-Intensity Transform GANs for High Fidelity Medical Image-to-Image Translation. International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI).
- Frid, P., Drake, M., Giese, A. K., Wasselius, J., Schirmer, M. D., Golland, P., et.al. (2020). Detailed phenotyping of posterior vs. anterior circulation ischemic stroke: a multi-center MRI study. Journal of Neurology 267 (3), 649-658.
- Zhang, M., Golland, P., Wells III, W. M., Fletcher, T. (2020). Low-dimensional shape analysis in the space of diffeomorphisms. Riemannian Geometric Statistics in Medical Image Analysis, 557-576.